rip: Identify Rank-Invariant Biomolcules for Use in Normalization
In pmartR/pmartRqc: Panomics Marketplace - Quality Control and Statistical Analysis for Panomics Data

View source: R/subset_funcs.R

rip	R Documentation

Identify Rank-Invariant Biomolcules for Use in Normalization

Description

Selects biomolecules for normalization via the method of rank-invariant biomolcules (RIP)

Usage

rip(e_data, edata_id, fdata_id, groupDF, alpha = 0.2)

Arguments

`e_data`	a `p \times n` data.frame, where `p` is the number of peptides, proteins, lipids, or metabolites and `n` is the number of samples. Each row corresponds to data for a peptide, protein, lipid, or metabolite, with one column giving the biomolecule identifier name.
`edata_id`	character string indicating the name of the peptide, protein, lipid, or metabolite identifier. Usually obtained by calling `attr(omicsData, "cnames")$edata_cname`.
`fdata_id`	character string indicating the name of the sample column name in f_data.
`groupDF`	data.frame created by `group_designation` with columns for sample.id and group. If two main effects are provided the original main effect levels for each sample are returned as the third and fourth columns of the data.frame.
`alpha`	numeric p-value threshold, above which the biomolecules are retained as rank invariant (default value 0.25)

Details

Biomolecules with complete data are subjected to a Kruskal-Wallis test (non-parametric one-way ANOVA) on group membership, and those biomolecules with p-value greater than a defined threshold alpha (common values include 0.1 or 0.25) are retained as rank-invariant biomolecules.